Read more about author Jeff Robbins. In the healthcare industry, surgical capacity management is one of the biggest issues organizations face. Hospitals and surgery centers must be efficient in handling their resources. The margins are too small for waste, and there are too many patients in need of care. Data, particularly real-time data, is an essential asset. But it is only useful if the pieces fit together, solving a puzzle…

Read more about author Doug Kimball. Knowledge graphs, while not as well-known as other data management offerings, are a proven dynamic and scalable solution for addressing enterprise data management requirements across several verticals. As a hub for data, metadata, and content, they provide a unified, consistent, and unambiguous view of data scattered across different systems. Using global knowledge as context for interpretation and a source for enrichment, they also optimize…

Read more about author Anastasios Arampatzis. There’s a unanimous consensus that data is the lifeblood of organizations. From customer records to intellectual property, the explosion of information creates tremendous value – and equally tremendous risk. The pace of cyberattacks accelerates relentlessly, with disastrous data breaches becoming a mainstay in news headlines and the associated costs skyrocketing. Current approaches to data security are woefully inadequate since they only partially address the evolving data…

Read more about author Pankaj Zanke. In the contemporary landscape of data-driven decision-making, enterprises are increasingly turning to predictive analytics to gain valuable insights into future trends and behaviors. Predictive analytics involves extracting patterns from historical data to forecast future outcomes, enabling organizations to make proactive decisions and optimize their operations. Traditionally, predictive analytics has been performed using standalone machine learning platforms, necessitating data extraction, preprocessing, modeling, and deployment pipelines.…